Statistical Perspectives in Machine Learning for Crop Recommendations

Agriculture stands as a vital component of human survival, contributing significantly to global economy. Even with its significance, there is a strong demand for advancements, especially with regard to crop recommendation systems. Accurate crop predictions play a vital role in boosting productivity, especially as climate change increasingly impacts crop production. Crop selection using traditional manual approaches based on soil and environmental characteristics has not worked well. Crop projections are highly dependent on a number of detailed factors, including soil properties, climatic patterns, temperature, rainfall, humidity, and geographic location. The creation of a recommendation system using different ML and DL approaches is the main goal of this chapter. Through the analysis of several criteria, the system seeks to recommend appropriate crops, assisting farmers in making well-informed decisions.This initiative holds promise for enhancing agricultural productivity and resilience in the face of evolving environmental challenges.